Total Portfolio Approach Requires Organizational Shift and AI Integration - Episode Hero Image

Total Portfolio Approach Requires Organizational Shift and AI Integration

Capital Allocators – Inside the Institutional Investment Industry · · Listen to Original Episode →
Original Title:

TL;DR

  • The Total Portfolio Approach (TPA) represents an "investor identity project" requiring real-time data and analytics to align all organizational goals, risk budgets, and liquidity needs, moving beyond traditional asset allocation.
  • Implementing TPA necessitates a fundamental organizational shift, demanding new analytics, incentive structures, and potentially a complete overhaul of how investment decisions are made and executed.
  • AI and advanced data analytics unlock "inference and insight" for investors, enabling them to move beyond mere speed improvements and discover novel patterns and knowledge within their data.
  • The future of investment offices will leverage AI for personalized guidance, acting like a sophisticated GPS that optimizes portfolio decisions based on unique investor profiles and goals, not just market opportunities.
  • Innovation in asset ownership is increasingly driven by "developmental investors" like Saudi Arabia's PIF and New Mexico's State Investment Council, who combine financial performance with societal or economic objectives.
  • True partnership between GPs and LPs involves GPs driving portfolio changes for LPs without direct compensation, demonstrating a commitment to the LP's success beyond contractual obligations.
  • Investing in early-stage "fund one" managers is crucial for building a thriving ecosystem, as these hungry founders are more receptive to innovation and offer capital efficiency compared to established funds.

Deep Dive

The adoption of a Total Portfolio Approach (TPA) signals a fundamental shift in institutional investing, moving beyond traditional asset allocation to an integrated investor identity project that leverages real-time data and advanced analytics. This evolution is driven by the need for greater portfolio precision and proactive management, but its successful implementation hinges on significant organizational change, particularly in data infrastructure and human capital. The implications are profound, demanding a redefinition of investment decision-making, compensation structures, and the very capabilities of investment offices.

The shift towards TPA requires building a central "nerve center" to align all portfolio activities with organizational goals, including risk budgets, liquidity needs, and available capabilities. This is inherently difficult, especially with the increasing allocation to private markets, where real-time valuation and data integration are challenging. Consequently, TPA is more readily applicable to organizations with less exposure to illiquid assets, or those willing to invest heavily in organizational capabilities to bridge this gap. The core of TPA is a move from "deal work" to "knowledge work," where investment decisions are informed by an intelligent understanding of "additionality" within the portfolio, allowing for more tactical and counter-cyclical moves based on real-time insights rather than static strategic allocations. This advanced level of investing, akin to the earlier adoption of asset-liability management, will likely become the standard for long-term investors.

The increasing integration of AI and data analytics is crucial to realizing TPA's potential. Beyond simple automation, AI offers the promise of enhanced insight and "inhuman intelligence" that can uncover novel patterns and optimize portfolio decisions. This moves investors from merely understanding their current exposures to predicting future outcomes and making granular, customized adjustments. For example, AI can act as an advanced navigation system for portfolios, considering not just the destination (goals) but also the "vehicle" (organizational capabilities) and real-time conditions (market data and risk factors) to provide unique guidance, preventing a homogenization of investment strategies. This capability is particularly beneficial for long-term investors who can allow insights to be fully priced into their portfolios.

Innovation in the allocator world is often driven by organizations tackling grand challenges, such as the Public Investment Fund (PIF) in Saudi Arabia aiming for net-zero emissions or the New Mexico State Investment Council leveraging subsoil assets for educational advancement and universal childcare. These developmental investors combine long-term objectives like economic diversification and social welfare with the pursuit of high performance, serving as potential role models for others. Similarly, PGGM's "3D TPA" (risk, return, and impact) demonstrates a complex organizational upgrade to provide unparalleled insights into long-horizon risks. The broader trend indicates a significant allocation of resources towards experimenting with AI, unlocking new capabilities for both internal analysis and external market engagement.

Within the venture capital space focused on "investech," critical innovations include real-time valuation tools for private equity and platforms like Hoopit and GrowthSphere that enhance internal knowledge management and network intelligence. These tools aim to improve operational efficiency, audit fees, and model organizational processes, serving as "red team" assistants for investment committees. However, significant weaknesses persist within traditional allocator structures, including bureaucratic processes, misaligned incentives, and a lack of technological expertise on boards. Overcoming these requires a deliberate focus on building an engine of innovation, which involves embracing messy processes, fostering a culture conducive to failure, and ensuring that governance structures include technologists alongside finance professionals. True partnership with GPs should extend beyond contractual terms to driving portfolio-level changes that benefit the LP, and a critical area for improvement is for asset owners to invest in early-stage managers (fund one) to cultivate a more dynamic and competitive ecosystem. Furthermore, developing talent within asset owner organizations is crucial, with initiatives like fellowships aiming to attract top graduates and build a pipeline of skilled professionals who can drive technological adoption and innovation.

Action Items

  • Create portfolio positioning system: Define 5 core data inputs (exposures, valuations, risk, liquidity, goals) for real-time asset allocation.
  • Audit 10 investment decision processes: Evaluate for bias towards knowledge work over deal work to support Total Portfolio Approach.
  • Implement AI simulation models: Target 3 key projection areas (market trends, risk factors, scenario analysis) to enhance investment insights.
  • Design incentive compensation framework: Align 3-5 key metrics with Total Portfolio Approach goals to foster systemic change.
  • Evaluate 5-10 GP relationships: Assess partnership depth beyond contracts, focusing on advice that drives portfolio change without direct payment.

Related Episodes

Key Quotes

"They have quietly become the most important organizations in the world, and I don't put a caveat on that one. They are the cornerstone of our modern social welfare state. They are integrated into so much policymaking, from Saudi Arabia to the United States to Australia. As banks have been regulated out of risk-taking, they have become the capital in capitalism."

Ashby Monk highlights the critical, yet often overlooked, role of large asset owners like pension funds and sovereign wealth funds. Monk argues that these organizations are foundational to social welfare and policy, and have become the primary source of capital in the economy as traditional banks have reduced risk-taking.

"I think of that as the beginnings of what we are now calling TPA. You need to understand the total portfolio. Every new investment that comes into the portfolio, you're thinking about the overall risk budget, liquidity needs, all these goals that every pension fund has. TPA begins to think about this not just as an asset allocation project. The word TPA to me feels more like an investor identity project."

Ashby Monk explains that the Total Portfolio Approach (TPA) evolved from earlier concepts like factor-based asset allocation. Monk posits that TPA moves beyond simply managing asset allocation to defining the fundamental identity of an investor, requiring consideration of the entire portfolio's risk, liquidity, and goals for every new investment.

"TPA, to the point of my life's work pivoting from pure governance to almost pure technology, getting TPA right means you have to build this nerve center at the center of the organization. You are aligning everything with an organization's goals. Our risk budget, liquidity, cash flows, capabilities, our people, everything is thinking about how this portfolio connects to our goals."

Ashby Monk emphasizes that implementing a Total Portfolio Approach (TPA) necessitates a significant technological infrastructure. Monk explains that TPA requires a central "nerve center" to align all organizational elements--risk, liquidity, capabilities, and people--with the overarching goals of the portfolio.

"The unit of work becomes knowledge work instead of deal work. The unit of work is different. It's not capital deployment, it's not bucket filling, it's something else moving you towards your objective, intelligent understanding of additionality in your portfolio."

Ashby Monk differentiates the work involved in a Total Portfolio Approach (TPA) from traditional strategic asset allocation. Monk argues that TPA shifts the focus from capital deployment and "bucket filling" to knowledge work, emphasizing an intelligent understanding of how new investments add value to the overall portfolio.

"The AlphaGo case study, you see this moment where inhuman intelligence revealed itself for the first time for most of us. The machine did a move that had never been trained on before. It was an inhuman move, move number 37. In fact, all the humans in the room thought it was a mistake. The move ended up to be the winning move."

Ashby Monk uses the AlphaGo example to illustrate the emergence of "inhuman intelligence" through AI. Monk explains that AlphaGo's unexpected, yet winning, move demonstrated AI's capacity to generate insights beyond human training and conventional understanding, marking a shift from speed to inference.

"The PIF, trillion-dollar-ish organization, started over 100 companies. This is a sovereign fund. Think about how different that is. This sovereign fund has started over 100 companies, even more than that. The Crown Prince of Saudi Arabia has said that he wants Saudi Arabia to be net zero by 2060. Saudi Arabia, that is synonymous with fossil fuels. For the Crown Prince to say, 'We're going to go to net zero by 2060,' and then point at the PIF and say, 'This is my lever for change,' we can all get excited about that opportunity to watch and see, can PIF take this place that is the global epicenter of fossil fuels and help turn it into a net zero economy?"

Ashby Monk highlights the Public Investment Fund (PIF) of Saudi Arabia as an example of an innovative asset owner undertaking significant developmental initiatives. Monk points to PIF's role in Saudi Arabia's ambitious goal of achieving net zero by 2060, despite the nation's historical reliance on fossil fuels, as a compelling example of using a sovereign fund as a catalyst for economic transformation.

"I am dyslexic. Came up quite strongly when I was first, second, third grade. This is the learn to read years. I was born in Edmonton, and my dad came down here to California in 1980, and I was four. I was part of a PhD thesis in the Stanford Medical School where they were studying dyslexia, how you help kids manage it."

Ashby Monk shares a personal detail about his dyslexia, explaining its early impact during his childhood. Monk recounts being part of a PhD thesis at Stanford Medical School that focused on helping children manage dyslexia, illustrating his long-standing engagement with the condition.

Resources

External Resources

Books

  • "Atomic Habits" by James Clear - Mentioned as an example of forming new habits by starting small.

People

  • Ashby Monk - Executive and research director of the Stanford Research Initiative on Long Term Investing, guest on the podcast.
  • Ted Sidis - Host of the Capital Allocators podcast.
  • Katie Milkman - Past guest who reminds listeners it's a good time for a fresh start and to form new habits.
  • Andrew Ang - Mentioned in relation to factor-based asset allocation.
  • Dimson - Mentioned in relation to factor-based asset allocation.
  • Joe Dear - Former CIO at CalPERS, discussed his ambition for factor-based asset allocation.
  • Steve Gilmore - Mentioned in relation to his move to CalPERS and the discussion of Total Portfolio Approach.
  • Jagdeep - Mentioned as trying to buy college leagues.
  • Prab R. Pulani - Mentioned as stating "I'll dare them to fire me" regarding innovation.
  • Joseph S. Signs - Of Fremont, co-author of a paper on neurodiversity.
  • Harrison Shaw - Founder of Shelton AI, passionate about aligning interests between LPs and GPs regarding fees and costs.

Organizations & Institutions

  • Stanford Research Initiative on Long Term Investing - Ashby Monk's affiliation.
  • KDX Management - Venture capital firm co-founded by Ashby Monk, focused on investech.
  • CalPERS - Mentioned in relation to attempts to implement Total Portfolio Approach and as a partner for a fellowship program.
  • Saudi Arabia's Public Investment Fund (PIF) - Flagged as an interesting sovereign fund taking on grand challenges, aiming for net zero by 2060.
  • New Mexico State Investment Council - Flagged as an interesting sovereign fund focused on education and universal childcare, funded by subsoil assets.
  • New Zealand Super Fund - Mentioned as a high-performing Total Portfolio investor.
  • Canada Pension Plan (CPP) - Mentioned as an example of a successful model for asset owners.
  • Australian Super Funds - Mentioned in relation to consolidation and competition driving innovation.
  • PGGM - Organization in the Netherlands launching its version of Total Portfolio Approach (3D TPA).
  • Los Alamos National Laboratory - Located in New Mexico, part of its ecosystem.
  • Sandia National Laboratories - Located in New Mexico, part of its ecosystem.
  • Yale University - Mentioned in relation to graduates and its venture capital focus.
  • Harvard University - Mentioned in relation to graduates.
  • Princeton University - Mentioned in relation to graduates.
  • University of California, Berkeley - Mentioned in relation to graduates and a former chancellor's comment.
  • Citadel - Mentioned as an alternative employer for a Stanford computer science graduate.
  • Orange County - Pension fund participating in a fellowship program.
  • Bridgewater - Mentioned in relation to its culture and radical candor.
  • Google - Mentioned in relation to its engineers, accommodations, and AI capabilities.
  • Facebook - Mentioned in relation to accommodations for engineers.
  • Ascension Data - Provides workflow software for compensation.
  • Bci (British Columbia Investment Management Corporation) - Co-author of an ESG paper.

Tools & Software

  • Hoopitt AI - Relationship intelligence platform mentioned.
  • Shelton AI - Company providing private equity real-time valuations.
  • Verifees - Feature of Shelton AI for real-time audit of fees and costs.
  • Growthsphere - Software that models an organization's investment process and can generate memos.

Articles & Papers

  • "The Technologized Investor" (2020) - Book by Dane R. Rook and an unnamed co-host, related to the "Technologized Podcast."

Websites & Online Resources

  • Capital Allocators - Podcast website.
  • SLTI (Stanford Long Term Investing) - Website hosting Stanford podcasts.
  • SSRN (Social Science Research Network) - Mentioned as a place where people read working papers.

Podcasts & Audio

  • Capital Allocators podcast - The podcast where this conversation is taking place.
  • "Don't Get Fired" podcast - Hosted by Ashby Monk and Prab R. Pulani, sharing stories of innovation in pension funds.
  • "The Technologized" podcast - Hosted by Ashby Monk and Dane R. Rook, explaining new technology to the investment audience.

Other Resources

  • Total Portfolio Approach (TPA) - Concept discussed as an advanced investor identity project, focusing on the entire portfolio's risk budget and liquidity needs.
  • Factor-based asset allocation - Concept discussed as a precursor to TPA, focusing on true nutrients of return.
  • Brinson work - Mentioned in relation to asset allocation being a driver of return.
  • Investech - Focus area for KDX Management.
  • AI (Artificial Intelligence) - Discussed in relation to unlocking additional basis points of return, speed, insight, and inhuman intelligence.
  • Portfolio Positioning System (PPS) - A system to understand a portfolio's current state and exposures.
  • ESG (Environmental, Social, and Governance) - Concept discussed in relation to financial performance uplift.
  • Neurodiversity - Discussed as a superpower and a pathway to alpha in the investment industry.
  • Categorical Advantages - Things an organization is born with, like location.
  • Cultivated Advantages - Advantages an organization has sought to build, like specific investment strategies.
  • 3D TPA (Three Dimensions Total Portfolio Approach) - PGGM's approach considering risk, return, and impact.

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